Coherence Theory of Truth as Base for Knowledge Based Systems
|
|
- Melissa Paul
- 5 years ago
- Views:
Transcription
1 Association for Information Systems AIS Electronic Library (AISeL) AMCIS 1996 Proceedings Americas Conference on Information Systems (AMCIS) Coherence Theory of Truth as Base for Knowledge Based Systems Heinz Josef Mubhoff Technische Univesitat Dresden, Follow this and additional works at: Recommended Citation Mubhoff, Heinz Josef, "Coherence Theory of Truth as Base for Knowledge Based Systems" (1996). AMCIS 1996 Proceedings This material is brought to you by the Americas Conference on Information Systems (AMCIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in AMCIS 1996 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact
2 Coherence Theory of Truth as Base for Knowledge Based Systems Heinz Josef Mußhoff Technische Universität Dresden Fakultät Wirtschaftswissenschaften Dresden, Germany A Special Problem of Expert Systems Usually knowledge based systems are realized as expert systems. Knowledge engineers try to build systems which 'represent' an expert's knowledge. These models typically are used by laymen lacking the specific expert knowledge in the modelized domain. Experts ared used to provide the knowledge to solve a specific problem and as a metaphor for constructing knowledge based systems. The later aspect has its roots in the psychological interest dominating research in artificial intelligence. Human problem solving behavior set artificial intelligence the example. The expert system approach satisfies many types of problems. But it can be shown that there are others which cannot be solved by this approach in a proper way. Today one special problem is that the expert system decides by its knowledge what is asked and what information is used for solving the problem. The user may provide data as input for the system - if the system asks for them - but nothing more. Some nice comedies deal with this situation, i. e. the doctor who does not pay any attention to the information his patient tells him and only does his routine job. In our days expert systems work in such a way. They are not able to react in an adaequate way, if their clients want to offer more than data for the problem solving process; they are not able to react on knowledge supplied by the user. But, there are many situations in problem solving where it is necessary that the client can offer more than just the data the system asks for. Let us have a look on problems in management, i. e. strategy formulation, and let us examine a consultation process in a firm. Who would be envolved? There may be an external consultant with special knowledge in strategic management, but who else? The answer may depend on the special problem which is focused on, but one can suppose it will be a manager who has his own special knowledge about strategy, markets etc. Maybe he has a very special opinion about it. But the consultant has to take care for it. He would be a bad consultant if he did not. A knowledge based system in many cases has to take care for the knowledge of his clients, too. But what is done with the knowledge from different sources? It may be in case of conflict, it may be cntradictory, inconsistent etc. Integration of Knowledge while Consulting What can be done when such situations with conflicting knowledge occur? Of course there may be many ways to solve that problem: One could say, in any way we accept the opinion of the consultant, because he is paid for his consultation and so we should use his knowledge. One could say, in any way we accept the opinion of the manager, because it is his firm and he has to take the responsibility for the strategy which will be realized.
3 One could look for a way to find a combination of competing knowledge. Perhaps one might thing about Hegel and his thesis, antithesis, synthesis model or something like this. When we are looking for cognitve solutions for a problem, then only the third approach is acceptable, although the others are relevant in real life. So one has to look for methods to find an acceptable combination of competing knowledge. For the further discussion I suggest to leave aside the expert system approach and all the cognitive psychology by which he is influenced. Knowledge is not only a problem in psychology. Knowledge has social aspects and there is a social system - science and arts - which is specialized in handling knowledge. What ideas can be found in science to work with knowledge? The (major) problem of (empirical) sciences is to determine what is truth - or better - what should be accepted as truth (at the moment). There are many different approaches to determine what should be said to be true. Perhaps one could say there are four main streams: Correspondence Theory of Truth, Pragmatic Theory of Truth, Intuitionistic Theory of Truth, Coherence Theory of Truth. Proponents of the Correnspondence Theory of Truth declare a sentence to be true if its content corresponds with the world. In the pragmatic sense one should regard a proposition to be true if the utility of its acceptance is greater than the one of its non-acceptance. In the intuitionistic theory there are two sorts of truths: primitive truth and inferred truths that can be achieved by an inferential machinery. Proponents of the Coherence Theory of Truth declare a sentence should be regarded true, if it can be accepted in our body of knowledge. True is what can be systematized. Knowlege is regarded as a system and science and arts care for it.1 Coherence Theory of Truth as a Mean for Systematization I like to concentrate my examination on Coherence Theory of Truth which usually is confronted to Correspondence Theory of Truth. A Correspondence Theory of Truth does not work in several situations, because oft its necessary connection to the real world, where special situations are not always present and so cannot be tested, i. e. a sentence with reference to the past. But, Coherence Theory of Truth - in my eyes - seems to be very attractive. I. e. one could look at our management problem as a process of combination, where knowledge of different sources (consultants, managers, etc.) is combined to find out what should be accepted as true. A very powerful version of Coherence Theory of Truth was developed by Nicholas Rescher.2 He shows the criteria one should use to do the job of knowledge systematization. The criteria should be used as regulative principle for for the systematization. Rescher mentions the following criteria to be relevant for systematization: completeness, cohesiveness, consonance,
4 functional regularity, functional simplicity and economy, functional efficiacy, wholeness, self-sufficiency, architectonic, functional unity, mutual supportiveness. Some of these criteria can be formalized to work in knowledge based systems. Others seem to be more informal and one has to look for an adaequate substitute. If this is done successfully, a knowledge base system could accept knowledge of the user at runtime while consultation. It could combine it to a new system of knowledge using the criteria or its substitutes. The Logic of Coherence Below I will describe the Logic of Coherence in a very short form. This is necessary for sketching an software architecture that will meet the requirements of the theory. In "Coherence Theory of Truth"3 (pp ) Rescher describes the search for truth in a coherentistic sense. The analysis starts with a set S of 'raw' data, the truth candidates. They are only candidates and not all data will be accepted as true. This set is the starting point of the analysis. Normally, not all elements of S can be true, because they may be in conflict. S is not necessarily consistent. Therefore the Set S has to be reduced. Here Rescher uses the concept of maximal consistent subsets (m.c.s.). Si is a m.c.s. of S if (1) it is not empty, (2) it is consistent, and (3) no S-element that is not already member of Si can be added to it without producing an inconsistency. Now, one can distinguish to sorts of elements: (1) elements which are member of all m.c.s. of S. They are called innocent-bystanders. (2) All other elements of S are called culprits. For every Si there is a set of its (logical) consequences C(Si). P is element of C(Si) iff it is the logical consequence of the conjunction of all the propositions of Si. The next step is do decide two sorts of consequences. A Consequence P might be an inevitable consequence (I-Consequence) of S iff P is a deductive consequence (L-consequence) of every m.c.s. Si of S. P is called a weak consequence (W-consequence) of the set S if there are some m.c.s. Si of S such that P is a logical consequence of Si. The next step is to decide what propositions should be accepted to be true. Generally one can say: No proposition should be accepted which does not follow from at least one m.c.s. Every proposition P which follows from every m.c.s. has to be accepted to be true. These statements mark an upper and lower limit for the decision which propositions which propositions should accepted to be true. Rescher uses the concept of the P-Consequence (preferential or plausible consequence) to intermediate these limits. He starts the determination of P-Consequences by selecting some m.c.s. which are called preferred m.c.s. P is called a P-Consequence of S if it follows from all the preferred m.c.s. of S. Rescher proposes to accept the P-Consequence as true relative to the 'raw' data S.
5 In 'Coherence Theory of Truth' Rescher mentions a number of methods to determine the preferred m.c.s., i. e.: Propositional Pivot-Points, Majority Rule, Probabilistic Preference, Plausibility Indexing, Most of these methods are formal and can be realized on a computer system. They use further knowledge to evaluate the m.c.s. which in many cases can be ask by the user of an information system. Sketch of a Knowledge Based System based on Coherence Theory of Truth In the following I will try to describe in a very short way an information system which will use some aspects of Rescher's Coherence Theory. (1) The starting point of such a system is a knowledge base. It contains generalized sentences about a special domain: theoretical and/or technological knowledge. The source of the knowlege is not import: experts, science, books etc. (2) A second component of the system is necessary to describe the problem which should be solved by the system. It is necessary for the description to meet the knowledge. (3) From the description and the generalized sentences of the knowledge base the system in relation to the problem desribed can instantiate special sentences. I call these sentences arguments. They are relevant only for the actual problem. The arguments must not be consistent and must not be accepted to be true. (4) From this set of all the derived arguments (and perhaps of the user arguments) maximal-consistent-sets are generated and presented to the user. (5) In a dialog the user and the system can evaluate the generated m.c.s. to derive preferred m.c.s. (6) All the arguments which can be derived from all preferred m.c.s. are presented as a solution of the problem. (7) The user may accept the presented solution. But, it may be the case that he rejects it, because of some special arguments he wants to supply by his own knowledge about the problem. Therefore a further system component is necessary to add arguments or even generalized sentences to the system. After adding the sentences to the system the process of generating m.c.s. (or - if necessary - arguments) starts again and a further solution (must not be another) is generated. (8) One critical point of the process is the evaluation of the m.c.s. It must be emphazised that it is an evaluation of sets by certain criteria not an evaluation of single arguments. Therefore it is rather difficult for an user to build his own solution from single arguments. There must be high coherence between the arguments. Further Prospects
6 There are some interesting side effects of such a system. It is easy to see, that if one implements and uses a knowledge based system based on Coherence Theory of Truth a special sort of learning or knowledge acquisiton can be realized. Because the system can use the knowledge acquired from a competent user, and systematized in the system's knowledge base for future consultations. There will be a richer fund of knowledge in future consultations. Another interesting aspect could be occur in the explanational skills of such a system. It can generate an explanation from out of the system the knowledge builts and will not be dependent on the trace of the fired rules. This is, because the solution of a problem in coherence theoretic approach is a system of arguments. References Further references available upon request from author. 1) Rescher, N.: The Coherence Theory of Truth. Oxford ) Rescher, N.: The Coherence Theory of Truth. Oxford Rescher, N.: Cognitive Systematization. A Systems-Theoretic Approach to a Coherentistic Theory of Knowledge. New York Rescher, N.: Induction. An essay on the justification of inductive reasoning. Oxford ) Rescher, N.: The Coherence Theory of Truth. Oxford 1973.
Audio: In this lecture we are going to address psychology as a science. Slide #2
Psychology 312: Lecture 2 Psychology as a Science Slide #1 Psychology As A Science In this lecture we are going to address psychology as a science. Slide #2 Outline Psychology is an empirical science.
More informationINTERVIEWS II: THEORIES AND TECHNIQUES 5. CLINICAL APPROACH TO INTERVIEWING PART 1
INTERVIEWS II: THEORIES AND TECHNIQUES 5. CLINICAL APPROACH TO INTERVIEWING PART 1 5.1 Clinical Interviews: Background Information The clinical interview is a technique pioneered by Jean Piaget, in 1975,
More informationPhenomenal content. PHIL April 15, 2012
Phenomenal content PHIL 93507 April 15, 2012 1. The phenomenal content thesis... 1 2. The problem of phenomenally silent contents... 2 3. Phenomenally sneaky contents... 3 3.1. Phenomenal content and phenomenal
More informationArtificial Intelligence Programming Probability
Artificial Intelligence Programming Probability Chris Brooks Department of Computer Science University of San Francisco Department of Computer Science University of San Francisco p.1/25 17-0: Uncertainty
More informationPlan Recognition through Goal Graph Analysis
Plan Recognition through Goal Graph Analysis Jun Hong 1 Abstract. We present a novel approach to plan recognition based on a two-stage paradigm of graph construction and analysis. First, a graph structure
More informationCognitive domain: Comprehension Answer location: Elements of Empiricism Question type: MC
Chapter 2 1. Knowledge that is evaluative, value laden, and concerned with prescribing what ought to be is known as knowledge. *a. Normative b. Nonnormative c. Probabilistic d. Nonprobabilistic. 2. Most
More informationArtificial Intelligence and Human Thinking. Robert Kowalski Imperial College London
Artificial Intelligence and Human Thinking Robert Kowalski Imperial College London 1 Artificial Intelligence and Human Thinking The Abductive Logic Programming (ALP) agent model as a unifying framework
More informationIII. WHAT ANSWERS DO YOU EXPECT?
III. WHAT ANSWERS DO YOU EXPECT? IN THIS CHAPTER: Theories and Hypotheses: Definitions Similarities and Differences Why Theories Cannot be Verified The Importance of Theories Types of Hypotheses Hypotheses
More informationAppearance properties
Appearance properties phil 93507 Jeff Speaks October 12, 2009 1 The role of appearance properties If we think that spectrum inversion/spectrum shift of certain sorts is possible, and that neither of the
More informationP(HYP)=h. P(CON HYP)=p REL. P(CON HYP)=q REP
BAYESIAN NETWORKS IN PHILOSOPHY STEPHAN HARTMANN, LUC BOVENS 1. Introduction There is a long philosophical tradition of addressing questions in philosophy of science and epistemology by means of the tools
More informationFunctionalist theories of content
Functionalist theories of content PHIL 93507 April 22, 2012 Let s assume that there is a certain stable dependence relation between the physical internal states of subjects and the phenomenal characters
More informationChapter 2. Knowledge Representation: Reasoning, Issues, and Acquisition. Teaching Notes
Chapter 2 Knowledge Representation: Reasoning, Issues, and Acquisition Teaching Notes This chapter explains how knowledge is represented in artificial intelligence. The topic may be launched by introducing
More informationCoaching, a scientific method
Coaching, a scientific method ROSELYNE KATTAR I. What is coaching? II. What is The Scientific Method in coaching? What are the phases of this process? III. How does a coach help his client? This article
More informationHypothesis-Driven Research
Hypothesis-Driven Research Research types Descriptive science: observe, describe and categorize the facts Discovery science: measure variables to decide general patterns based on inductive reasoning Hypothesis-driven
More informationDEVELOPING THE RESEARCH FRAMEWORK Dr. Noly M. Mascariñas
DEVELOPING THE RESEARCH FRAMEWORK Dr. Noly M. Mascariñas Director, BU-CHED Zonal Research Center Bicol University Research and Development Center Legazpi City Research Proposal Preparation Seminar-Writeshop
More informationOverview. cis32-spring2003-parsons-lect15 2
EXPERT SYSTEMS Overview The last lecture looked at rules as a technique for knowledge representation. In a while we will go on to look at logic as a means of knowledge representation. First, however, we
More informationOverview EXPERT SYSTEMS. What is an expert system?
EXPERT SYSTEMS Overview The last lecture looked at rules as a technique for knowledge representation. In a while we will go on to look at logic as a means of knowledge representation. First, however, we
More informationAssignment 4: True or Quasi-Experiment
Assignment 4: True or Quasi-Experiment Objectives: After completing this assignment, you will be able to Evaluate when you must use an experiment to answer a research question Develop statistical hypotheses
More informationA Difference that Makes a Difference: Welfare and the Equality of Consideration
84 A Difference that Makes a Difference: Welfare and the Equality of Consideration Abstract Elijah Weber Philosophy Department Bowling Green State University eliweber1980@gmail.com In Welfare, Happiness,
More informationThe Logic of Data Analysis Using Statistical Techniques M. E. Swisher, 2016
The Logic of Data Analysis Using Statistical Techniques M. E. Swisher, 2016 This course does not cover how to perform statistical tests on SPSS or any other computer program. There are several courses
More informationWhy Is It That Men Can t Say What They Mean, Or Do What They Say? - An In Depth Explanation
Why Is It That Men Can t Say What They Mean, Or Do What They Say? - An In Depth Explanation It s that moment where you feel as though a man sounds downright hypocritical, dishonest, inconsiderate, deceptive,
More informationIncluding Quantification in Defeasible Reasoning for the Description Logic EL
Including Quantification in Defeasible Reasoning for the Description Logic EL Maximilian Pensel and Anni-Yasmin Turhan Institute for Theoretical Computer Science, Technische Universität Dresden first-name.last-name
More informationCHAPTER 2 APPLYING SCIENTIFIC THINKING TO MANAGEMENT PROBLEMS
Cambodian Mekong University is the university that cares for the value of education MN 400: Research Methods CHAPTER 2 APPLYING SCIENTIFIC THINKING TO MANAGEMENT PROBLEMS Teacher: Pou, Sovann Sources of
More informationSystems Theory: Should Information Researchers Even Care?
Association for Information Systems AIS Electronic Library (AISeL) SAIS 2016 Proceedings Southern (SAIS) 2016 Systems Theory: Should Information Researchers Even Care? Kane J. Smith Virginia Commonwealth
More informationCOHERENCE: THE PRICE IS RIGHT
The Southern Journal of Philosophy Volume 50, Issue 1 March 2012 COHERENCE: THE PRICE IS RIGHT Paul Thagard abstract: This article is a response to Elijah Millgram s argument that my characterization of
More informationTheory Building and Hypothesis Testing. POLI 205 Doing Research in Politics. Theory. Building. Hypotheses. Testing. Fall 2015
and and Fall 2015 and The Road to Scientific Knowledge and Make your Theories Causal Think in terms of causality X causes Y Basis of causality Rules of the Road Time Ordering: The cause precedes the effect
More informationARE EX-ANTE ENHANCEMENTS ALWAYS PERMISSIBLE?
ARE EX-ANTE ENHANCEMENTS ALWAYS PERMISSIBLE? forthcoming in the American Journal of Bioethics S. Matthew Liao, D. Phil. Phoebe R. Berman Bioethics Institute Johns Hopkins University Baltimore, MD 21205
More informationHow to stop Someone who is ADDICTED ENABLING
stop ENABLING Table of Contents 2 Are You an Enabler? What if the steps you were taking to help a friend or family member through a problem or crisis were actually the very things hurting them most? And,
More informationModeling and Environmental Science: In Conclusion
Modeling and Environmental Science: In Conclusion Environmental Science It sounds like a modern idea, but if you view it broadly, it s a very old idea: Our ancestors survival depended on their knowledge
More informationThe science of the mind: investigating mental health Treating addiction
The science of the mind: investigating mental health Treating addiction : is a Consultant Addiction Psychiatrist. She works in a drug and alcohol clinic which treats clients from an area of London with
More informationConsider the following aspects of human intelligence: consciousness, memory, abstract reasoning
All life is nucleic acid. The rest is commentary. Isaac Asimov Consider the following aspects of human intelligence: consciousness, memory, abstract reasoning and emotion. Discuss the relative difficulty
More informationArtificial Intelligence: Its Scope and Limits, by James Fetzer, Kluver Academic Publishers, Dordrecht, Boston, London. Artificial Intelligence (AI)
Artificial Intelligence: Its Scope and Limits, by James Fetzer, Kluver Academic Publishers, Dordrecht, Boston, London. Artificial Intelligence (AI) is the study of how to make machines behave intelligently,
More informationNegotiation Frames. Michael Rovatsos. February 5, 2004
Lehrstuhl für Theoretische Informatik und Grundlagen der Künstlichen Intelligenz Fakultät für Informatik, Technische Universität München February 5, 2004 main in m 2 inffra Motivation Motivation in m 2
More information[a] relationship between two variables in which a change or variation in one variables produces a change or variation in a second variable.
CAUSATION According to Guppy, causation is: [a] relationship between two variables in which a change or variation in one variables produces a change or variation in a second variable. Four cr iteria ares
More informationThe Fallacy of Taking Random Supplements
The Fallacy of Taking Random Supplements Healthview interview with Dr. Paul Eck Healthview: We can see from our conversations that you are totally against people taking random supplements even if people
More informationA conversation with Professor David Chalmers, May 20, 2016 Participants
A conversation with Professor David Chalmers, May 20, 2016 Participants Professor David Chalmers Professor of Philosophy, New York University (NYU) Luke Muehlhauser Research Analyst, Open Philanthropy
More informationPsychology Research Process
Psychology Research Process Logical Processes Induction Observation/Association/Using Correlation Trying to assess, through observation of a large group/sample, what is associated with what? Examples:
More informationLEARNING. Learning. Type of Learning Experiences Related Factors
LEARNING DEFINITION: Learning can be defined as any relatively permanent change in behavior or modification in behavior or behavior potentials that occur as a result of practice or experience. According
More informationAssessing the Foundations of Conscious Computing: A Bayesian Exercise
Assessing the Foundations of Conscious Computing: A Bayesian Exercise Eric Horvitz June 2001 Questions have long been posed with about whether we might one day be able to create systems that experience
More informationPlan Recognition through Goal Graph Analysis
Plan Recognition through Goal Graph Analysis Jun Hong 1 Abstract. We present a novel approach to plan recognition based on a two-stage paradigm of graph construction and analysis. First, a graph structure
More informationGold and Hohwy, Rationality and Schizophrenic Delusion
PHIL 5983: Irrational Belief Seminar Prof. Funkhouser 2/6/13 Gold and Hohwy, Rationality and Schizophrenic Delusion There are two plausible departments of rationality: procedural and content. Procedural
More informationTheory Program Transcript
Theory Program Transcript [MUSIC] NARRATOR: What is theory and how does theory relate to the various methods of research design? In this video program, Dr. Michael Patton explores the answers to these
More informationThinking and Intelligence
Thinking and Intelligence Learning objectives.1 The basic elements of thought.2 Whether the language you speak affects the way you think.3 How subconscious thinking, nonconscious thinking, and mindlessness
More informationPOLI 343 Introduction to Political Research
POLI 343 Introduction to Political Research Session 5: Theory in the Research Process, Concepts, Laws and Paradigms Lecturer: Prof. A. Essuman-Johnson, Dept. of Political Science Contact Information: aessuman-johnson@ug.edu.gh
More informationDeliberating on Ontologies: The Present Situation. Simon Milton Department of Information Systems, The University of Melbourne
Deliberating on Ontologies: The Present Situation Simon Milton Department of, The University of Melbourne 1. Helping data models better map the world 2. Finding the role of ontology where theories of agency
More informationScience, Society, and Social Research (1) Benjamin Graham
Science, Society, and Social Research (1) Nuts and Bolts My computer croaked, so no clickers today We will start collecting clicker data for grades next Thurs Discussion sections start next week Homework
More informationPSYCHOLOGICAL CONSCIOUSNESS AND PHENOMENAL CONSCIOUSNESS. Overview
Lecture 28-29 PSYCHOLOGICAL CONSCIOUSNESS AND PHENOMENAL CONSCIOUSNESS Overview David J. Chalmers in his famous book The Conscious Mind 1 tries to establish that the problem of consciousness as the hard
More informationEffective Intentions: The Power of Conscious Will
Book Review Effective Intentions: The Power of Conscious Will Alfred R. Mele Oxford University Press, Oxford, 2009 Marco Fenici* fenici@unisi.it Mele s book is a concise analysis of much research in neurophysiology
More informationDesign Methodology. 4th year 1 nd Semester. M.S.C. Madyan Rashan. Room No Academic Year
College of Engineering Department of Interior Design Design Methodology 4th year 1 nd Semester M.S.C. Madyan Rashan Room No. 313 Academic Year 2018-2019 Course Name Course Code INDS 315 Lecturer in Charge
More informationSleeping Beauty is told the following:
Sleeping beauty Sleeping Beauty is told the following: You are going to sleep for three days, during which time you will be woken up either once Now suppose that you are sleeping beauty, and you are woken
More informationUNDERSTANDING THEORETICAL & CONCEPTUAL FRAMEWORKS
UNDERSTANDING THEORETICAL & CONCEPTUAL FRAMEWORKS 1 Concepts Generalized idea about a class of objects, attributes, occurrences or process that has been given a name. Examples: Fruit leadership Innovation
More informationRepresentation Theorems for Multiple Belief Changes
Representation Theorems for Multiple Belief Changes Dongmo Zhang 1,2 Shifu Chen 1 Wujia Zhu 1,2 Zhaoqian Chen 1 1 State Key Lab. for Novel Software Technology Department of Computer Science and Technology
More informationRunning Head: NARRATIVE COHERENCE AND FIDELITY 1
Running Head: NARRATIVE COHERENCE AND FIDELITY 1 Coherence and Fidelity in Fisher s Narrative Paradigm Amy Kuhlman Wheaton College 13 November 2013 NARRATIVE COHERENCE AND FIDELITY 2 Abstract This paper
More informationProgramming with Goals (3)
Programming with Goals (3) M. Birna van Riemsdijk, TU Delft, The Netherlands GOAL slides adapted from MAS course slides by Hindriks 4/24/11 Delft University of Technology Challenge the future Outline GOAL:
More informationEffect of drug abuse on individual >>>CLICK HERE<<<
Effect of drug abuse on individual >>>CLICK HERE
More informationHow Does Analysis of Competing Hypotheses (ACH) Improve Intelligence Analysis?
How Does Analysis of Competing Hypotheses (ACH) Improve Intelligence Analysis? Richards J. Heuer, Jr. Version 1.2, October 16, 2005 This document is from a collection of works by Richards J. Heuer, Jr.
More informationChapter 02 Developing and Evaluating Theories of Behavior
Chapter 02 Developing and Evaluating Theories of Behavior Multiple Choice Questions 1. A theory is a(n): A. plausible or scientifically acceptable, well-substantiated explanation of some aspect of the
More informationThere is nothing as practical as good theory?! Preliminary consideration of historical and recent basics, exemplified by environmental education
There is nothing as practical as good theory?! Preliminary consideration of historical and recent basics, exemplified by environmental education Lilian Fried 18 TH EECERA ANNUAL CONFERENCE Stavanger, Norway
More information9699 SOCIOLOGY. Mark schemes should be read in conjunction with the question paper and the Principal Examiner Report for Teachers.
CAMBRIDGE INTERNATIONAL EXAMINATIONS GCE Advanced Subsidiary Level and GCE Advanced Level MARK SCHEME for the May/June 2014 series 9699 SOCIOLOGY 9699/23 Paper 2 (Theory and Methods), maximum raw mark
More informationA Computational Theory of Belief Introspection
A Computational Theory of Belief Introspection Kurt Konolige Artificial Intelligence Center SRI International Menlo Park, California 94025 Abstract Introspection is a general term covering the ability
More informationProblem Situation Form for Parents
Problem Situation Form for Parents Please complete a form for each situation you notice causes your child social anxiety. 1. WHAT WAS THE SITUATION? Please describe what happened. Provide enough information
More information102 HORNBILL. 4. Essay-writing
102 HORNBILL 4. Essay-writing MOST of us find it difficult to begin writing. We can make this easier by thinking about the topic either through brainstorming, that is with several people in a group giving
More informationOntology of Observing: The Biological Foundations of Self-Consciousness and of The Physical Domain of Existence
Ontology of Observing: The Biological Foundations of Self-Consciousness and of The Physical Domain of Existence Humberto R. Maturana (1988) Contents 1 Purpose 3 2 The problem 3 3 Nature of the answer 3
More informationChapter Nine The Categorization and Evaluation Exercise
Chapter Nine, The Categorization and Evaluation Exercise, 1 Chapter Nine The Categorization and Evaluation Exercise Revisiting your Working Thesis Why Categorize and Evaluate Evidence? Dividing, Conquering,
More informationThe Art of Diplomacy
The Art of Diplomacy School Research Nexus Don W. Hooper, Ph.D. Washington DC July 7, 2017 Kind Assertion of Ideas and Opinions Tact and diplomacy are methods used to aid effective communication, especially
More informationJerry R. Hobbs. SRI International. Menlo Park, California. rules operating at a symbolic level intermediate between neurophysiology
Matter, Levels, and Consciousness Jerry R. Hobbs SRI International Menlo Park, California Searle's ontology is at once richer and more barren than that of most cognitive scientists. He says repeatedly
More informationPsychology Research Process
Psychology Research Process Logical Processes Induction Observation/Association/Using Correlation Trying to assess, through observation of a large group/sample, what is associated with what? Examples:
More informationEcon 270: Theoretical Modeling 1
Econ 270: Theoretical Modeling 1 Economics is certainly not the only social science to use mathematical theoretical models to examine a particular question. But economics, since the 1960s, has evolved
More informationProcessing of Logical Functions in the Human Brain
Processing of Logical Functions in the Human Brain GRMELA ALEŠ AGCES Ltd. AGCES, Levského 3221/1, Praha 4 CZECH REPUBLIC N. E. MASTORAKIS Military Institutions of University Education, Hellenic Naval Academy,
More informationRecognizing Ambiguity
Recognizing Ambiguity How Lack of Information Scares Us Mark Clements Columbia University I. Abstract In this paper, I will examine two different approaches to an experimental decision problem posed by
More informationChapter 1 Introduction to Educational Research
Chapter 1 Introduction to Educational Research The purpose of Chapter One is to provide an overview of educational research and introduce you to some important terms and concepts. My discussion in this
More informationAnswers to Midterm Exam
Answers to Midterm Exam Econ 159a/MGT522a Ben Polak Fall 2007 The answers below are more complete than required to get the points. In general, more concise explanations are better. Question 1. [15 total
More informationInsight Assessment Measuring Thinking Worldwide
California Critical Thinking Skills Test (CCTST). The CCTST measures the reasoning skills human beings use in the process of reflectively deciding what to believe or what to do. Skill/Attribute Name SE
More informationAn Approach To Develop Knowledge Modeling Framework Case Study Using Ayurvedic Medicine
251 An Approach To Develop Knowledge Modeling Framework Case Study Using Ayurvedic Medicine D.S. Kalana Mendis *, Asoka S. Karunananda +, and U. Samarathunga ++ * Department of Information Technology,
More informationIncorporating Action into Diagnostic Problem Solving (An Abridged Report)
Incorporating Action into Diagnostic Problem Solving (An Abridged Report) Sheila A. McIlraith Department of Computer Science, University of Toronto Toronto, ON M5S 1A4 Canada e-mail: mcilrait@cs.toronto.edu
More informationValue of emotional intelligence in veterinary practice teams
Vet Times The website for the veterinary profession https://www.vettimes.co.uk Value of emotional intelligence in veterinary practice teams Author : MAGGIE SHILCOCK Categories : Vets Date : February 17,
More informationA Cooperative Multiagent Architecture for Turkish Sign Tutors
A Cooperative Multiagent Architecture for Turkish Sign Tutors İlker YILDIRIM Department of Computer Engineering Bogazici University, Bebek, 34342, Turkey ilker.yildirim@boun.edu.tr EASSS 2008 1 Outline
More informationAbstracts. An International Journal of Interdisciplinary Research. From Mentalizing Folk to Social Epistemology
Proto Sociology s An International Journal of Interdisciplinary Research 3 Vol. 16, 2002 Understanding the Social: New Perspectives from Epistemology Contents From Mentalizing Folk to Social Epistemology
More informationStep 2 Challenging negative thoughts "Weeding"
Managing Automatic Negative Thoughts (ANTs) Step 1 Identifying negative thoughts "ANTs" Step 2 Challenging negative thoughts "Weeding" Step 3 Planting positive thoughts 'Potting" Step1 Identifying Your
More informationCase study. The Management of Mental Health at Work at Brentwood Community Print
Case study The Management of Mental Health at Work at Brentwood Community Print This case study looks at how a Community Interest Company (CIC) in the printing sector has used its expertise to support
More informationChapter 12. The One- Sample
Chapter 12 The One- Sample z-test Objective We are going to learn to make decisions about a population parameter based on sample information. Lesson 12.1. Testing a Two- Tailed Hypothesis Example 1: Let's
More informationConducting Research in the Social Sciences. Rick Balkin, Ph.D., LPC-S, NCC
Conducting Research in the Social Sciences Rick Balkin, Ph.D., LPC-S, NCC 1 Why we do research Improvement Description Explanation Prediction R. S. Balkin, 2008 2 Theory Explanation of an observed phenomena
More information2014 Philosophy. National 5. Finalised Marking Instructions
National Qualifications 2014 2014 Philosophy National 5 Finalised Marking Instructions Scottish Qualifications Authority 2014 The information in this publication may be reproduced to support SQA qualifications
More informationKnowledge is rarely absolutely certain. In expert systems we need a way to say that something is probably but not necessarily true.
CmSc310 Artificial Intelligence Expert Systems II 1. Reasoning under uncertainty Knowledge is rarely absolutely certain. In expert systems we need a way to say that something is probably but not necessarily
More informationThe Scientific Method
Course "Empirical Evaluation in Informatics" The Scientific Method Prof. Dr. Lutz Prechelt Freie Universität Berlin, Institut für Informatik http://www.inf.fu-berlin.de/inst/ag-se/ Science and insight
More informationThe Power of Feedback
The Power of Feedback 35 Principles for Turning Feedback from Others into Personal and Professional Change By Joseph R. Folkman The Big Idea The process of review and feedback is common in most organizations.
More informationMyers-Briggs Type Indicator. Individual & Family Dynamics 12 Mr. Rich 2014
Myers-Briggs Type Indicator Individual & Family Dynamics 12 Mr. Rich 2014 History 1917 - As a hobby, Katharine Briggs starts researching personality. Briggs determines 4 personality types while studying
More informationA Cooperative Multiagent Architecture for Turkish Sign Tutors
A Cooperative Multiagent Architecture for Turkish Sign Tutors İlker Yıldırım Department of Computer Engineering Boğaziçi University Bebek, 34342, Istanbul, Turkey ilker.yildirim@boun.edu.tr 1 Introduction
More informationExpanding Comparative Literature into Comparative Sciences Clusters with Neutrosophy and Quad-stage Method
New Trends in Neutrosophic Theory and Applications FU YUHUA CNOOC Research Institute, Beijing, 100028, China. E-mail: fuyh1945@sina.com Expanding Comparative Literature into Comparative Sciences Clusters
More informationThinking Like a Researcher
3-1 Thinking Like a Researcher 3-3 Learning Objectives Understand... The terminology used by professional researchers employing scientific thinking. What you need to formulate a solid research hypothesis.
More informationEquine Assisted Psychotherapy and Addictions Recovery. NAADAC Conference ~~~~ September 28, 2014
Equine Assisted Psychotherapy and Addictions Recovery NAADAC Conference ~~~~ September 28, 2014 Lynn Moore MA, LADC, CCDP, EAGALA Advanced Certified, EAGALA Mentor/Trainer Heather Jeffrey EAGALA Advanced
More informationGeneralization and Theory-Building in Software Engineering Research
Generalization and Theory-Building in Software Engineering Research Magne Jørgensen, Dag Sjøberg Simula Research Laboratory {magne.jorgensen, dagsj}@simula.no Abstract The main purpose of this paper is
More information6. A theory that has been substantially verified is sometimes called a a. law. b. model.
Chapter 2 Multiple Choice Questions 1. A theory is a(n) a. a plausible or scientifically acceptable, well-substantiated explanation of some aspect of the natural world. b. a well-substantiated explanation
More informationEinführung in Agda. Peter Thiemann. Albert-Ludwigs-Universität Freiburg. University of Freiburg, Germany
Einführung in Agda https://tinyurl.com/bobkonf17-agda Albert-Ludwigs-Universität Freiburg Peter Thiemann University of Freiburg, Germany thiemann@informatik.uni-freiburg.de 23 Feb 2018 Programs that work
More informationConfirmation 4 Reasoning by Analogy; Nicod s Condition
Confirmation 4 Reasoning by Analogy; Nicod s Condition (pp. 11 14) Patrick Maher Philosophy 471 Fall 2006 Reasoning by analogy If two individuals are known to be alike in certain respects, and one is found
More informationIs it possible to give a philosophical definition of sexual desire?
Issue 1 Spring 2016 Undergraduate Journal of Philosophy Is it possible to give a philosophical definition of sexual desire? William Morgan - The University of Sheffield pp. 47-58 For details of submission
More informationQ: What can you tell us about the work you do and your involvement with children with autism?
If you know one person with autism, you know one person with autism April is Autism Awareness & Acceptance month and in an attempt to further educate the public about autism, Catriona Monthy, a registered
More informationZen and the Art of Explaining the Mind
Harnad, S. (2011) Zen and the Art of Explaining the Mind. International Journal of Machine Consciousness (IJMC) (forthcming). [Review of Shanahan M. (2010) Embodiment and the Inner Life: Cognition and
More informationEmpty Thoughts: An Explanatory Problem for Higher-Order Theories of Consciousness
Empty Thoughts: An Explanatory Problem for Higher-Order Theories of Consciousness word count: 2,420 Abstract Block (2011) has recently argued that empty higher-order representations raise a problem for
More informationMore about inferential control models
PETROCONTROL Advanced Control and Optimization More about inferential control models By Y. Zak Friedman, PhD Principal Consultant 34 East 30 th Street, New York, NY 10016 212-481-6195 Fax: 212-447-8756
More information